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Insomnia and distress as mediators on the relationship from cyber-victimization to self-reported psychotic experiences: a binational study from Tunisia and Lebanon

Abstract

Background

While expansive research has accumulated concerning the association between traditional, face-to-face peer victimization and psychosis, a paucity of empirical research has been undertaken so far to investigate these associations with experiences of new and evolving ways of victimization through the digital world. Exploring these associations is highly relevant and timely, given that emerging adults are heavy users of digital technologies, highly exposed to online risks, and are at the peak age of onset of psychosis. This study aimed to test the hypothesis that psychological distress and insomnia symptoms have a significant indirect mediating effect on the association between cyber-victimization and self-reported positive psychotic experiences (SRPEs) in a binational sample of Tunisian and Lebanese community adults.

Method

The total sample was composed of 3766 participants; 3103 were from Lebanon (Mean age: 21.73 ± 3.80 years, 63.6% females) and 663 from Tunisia (Mean age: 26.32 ± 4.86 years, 59.9% females). Online anonymous self-report questionnaires were administered to all participants.

Results

Higher SRPEs were found in Lebanese participants compared to Tunisians, in single participants compared to married ones, in those with a university level of education compared to secondary or less, in those who live in rural areas compared to urban, in those who do not smoke, do not drink alcohol and do not use marijuana or any other illegal drug. Furthermore, more cyber-victimization, a higher insomnia severity and psychological distress were significantly associated with higher SRPEs. After adjusting for potential confounders, mediation analysis demonstrated that higher cyber-victimization was significantly associated with more insomnia severity/psychological distress; which were, in turn, significantly associated with greater SRPEs. Finally, more cyber-victimization was significantly and directly associated with more positive dimension.

Conclusion

Identifying insomnia and distress as mediators could provide novel insight for psychosis prevention efforts and intervention targets for cyber-victimized individuals prone to experience subclinical psychotic symptoms.

Peer Review reports

Background

The dimensional approach states that the psychosis phenotype exists on a continuum across the community, with psychotic experiences (PEs) being at the milder end, and severe debilitating psychotic disorders being at the highest end of the continuum [1, 2]. PEs refer to subclinical psychotic symptoms (perceptual abnormalities and delusional beliefs) seen in non-clinical individuals, that could cause distress and interfere with daily functioning, but generally do not motivate help-seeking [3,4,5]. There is sufficiently strong epidemiological evidence that PEs are relatively highly prevalent in general population samples [6,7,8,9]; and are implicated in predicting other psychopathology and behavioral problems’ onset [10, 11], thereby contributing to high mental health services use and increased healthcare costs [12, 13].

Different methodologies exist for evaluating PEs. PEs can either be assessed by self-report (reflecting clinically non-confirmed self-reported PEs) and/or structured clinical interviews (reflecting clinically relevant PEs) [6]. Both methods have been shown to describe phenotypes pertaining to the same spectrum phenotype (i.e., clinical psychosis) [14]. Indeed, several validation studies provided evidence for the predictive validity of self-report measures of PEs against clinical judgment (e.g., [15, 16]). We focused in the present study on self-reported PEs (SRPEs). More recent research demonstrated that individuals who self-reported frequent and distressing SRPEs, even when not validated in structured clinical assessments, were associated with increased risk of mental health problems; which suggests that both SRPEs and PEs assessed by clinical judgment reflect the same underlying construct [14]. The SRPEs construct was found to be associated with family history for psychotic disorders and environmental risk factors for psychosis [17, 18]. In addition, baseline SRPEs have consistently been shown to confer an increased risk for developing a psychotic disorder outcome [6]; thus representing an important clinical phenotype for early intervention [14]. According to the psychosis proneness-persistence-impairment model by van Os et al. [3], PEs represent a “transitory developmental expression of psychosis” that might change over the individual life span to become abnormally persistent and impairing, depending on additional environmental exposure interacting with genetic risk. Interestingly however, a recent Swedish twin study [19] demonstrated that exposure to negative environmental factors (such as bullying) plays a greater role in the etiology of PEs than genetic factors, which further supports the major importance of the diathesis-stress model [20] for understanding PEs. Identifying how environmental factors can affect SRPEs can advance our knowledge of the mechanisms underlying psychosis proneness, and provide novel perspectives for prevention and early intervention strategies in psychosis. To this end, this study proposes to investigate the interplay between cyber-victimization and SRPEs.

The relationship between cyber-victimization and SRPEs

Cyber-victimization (also called Internet or electronic victimization) is a new form of peer victimization referring to repeated and willful harassment (e.g., nasty comments, threats, humiliation, or exclusion) inflicted through information and communication technologies [21,22,23,24]. Cyber-victimization is a highly prevalent problem worldwide, affecting up to 73.5% adolescents and young adults [25, 26]. A growing body of knowledge suggests that cyber-victimization tend to target same victims as traditional bullying [27]; and that reported detrimental impact of both forms of victimization appears similar, such as suicidality [28], depression, low self-esteem [29], feeling unsafe at school, conduct problems, hyperactivity and peer problems [30], psychosomatic problems [30], and substance use [31]. This has led some authors to suggest that cyber-victimization can be viewed as “an extension” of face-to-face bullying victimization [32]. However, approaching the concept of cyber-victimization as a sub-category of in-real-life victimization might result in drastically underestimating its prevalence and negative consequences on mental health [33]. For example, while extensive evidence has shown that traditional bullying victimization increases the risk of later development of psychotic symptoms [34,35,36,37], such evidence is lacking for cyber-victimization. There is some emerging evidence in favor of differential effects of cyber- and traditional victimization [38]. There appears to be a worse impact on mental health and greater threats to psychosocial adaptation caused by cyber forms of victimization compared to traditional ones [39,40,41]. These data highlight the need for investigating the traditionally well-established relationship bullying-psychosis [34, 36, 42,43,44] with the new, online form of victimization.

Scant research has focused on the relationship between cyber-victimization and the psychotic phenomena in clinical and non-clinical populations. We could identify only four studies focusing on the relationship between cyber-victimization and psychotic symptoms [45,46,47,48]. Two of these studies specifically focused on SRPEs. The first study found that being a cyberbully or cyber-victim was associated with more severe SRPEs in healthy adolescents [47]. Similarly, the second study showed that being involved in cyberbullying was associated with greater psychoticism [48]. Multiple potential theoretically-driven mechanisms could be advanced to explain the relationship between cybervictimization and psychosis. The first theoretical explanation stipulates that some personal characteristics (e.g., pre-existing adjustment difficulties [49, 50]; impaired socio-emotional skills [51, 52]; attachment adversity [53, 54]) might enhance the likelihood of both being victimized and developing psychosis. The second hypothesized mechanism is that cyber-victimization and psychosis share a number of environmental factors, such as a precarious socioeconomic status [55, 56], low social support [57, 58]. Another mechanism can be suggested by analogy based on twin studies that documented shared genetic factors influencing risks for experiencing peer victimization and developing later SRPEs (e.g., [59]); but such evidence has yet to be demonstrated for cyber forms of victimization. Finally, plausible biological mechanisms to explain pathways linking cybervictimization to psychosis can be proposed, such as a disrupted functioning of the hypothalamic-pituitary-adrenal (HPA) axis [60, 61]. Overall, very little is known about the nature and mechanisms behind the relationship cybervictimization-SRPEs. To gain insight into the possible underlying pathways of this relationship, we hypothesized that psychological distress (i.e., depression, anxiety, stress) and insomnia symptoms have an indirect effect on the association between cyber-victimization and positive SRPEs.

Distress and insomnia as mediators

Cyber-victimization seems to be a marker of more severe psychological distress. For instance, a recent metaanalysis encompassing 42 studies and 266,888 individuals (aged 8–20 years) estimated that cyber-victimization is associated with a unique 3.38-fold increased risk of depression [62]. Other meta-analyses’ findings have indicated that cyberbullying leads to anxiety symptoms [63]. It has also been stated that cyber-victimization poses a threat to belonging [64], contributing, in turn, to increased levels of stress [65]. A study found, for example, that being cyber-victimized (i.e., verbally harassed and socially excluded) has been associated with acute stress reactions [66]. Additionally, a longitudinal study demonstrated that cyber-victimization predicted depression and anxiety at 12 months follow-up, and that the positive prospective link between cyber-victimization and subsequent depression was stronger in individuals who experienced high perceived stress [66]. At the same time, psychological distress was shown to be significantly and positively correlated with increased psychosis risk, subthreshold psychotic symptoms, and an elevated risk of transition from high-risk states to a sustained psychosis [67, 68]. In particular, there is evidence from longitudinal research suggesting that depression is associated with subsequent psychotic symptoms in both clinical [69] and non-clinical populations [70, 71].

On the other hand, it has been argued that individuals targeted by different sorts of intended online aggressions, especially in the hours before bed, may struggle with initiating or maintaining sleep [72]. A large population-based study among Finnish adolescents found that being a cyber-victim was significantly associated with sleep problems [73]. A French study found that cyber-victimized high school adolescents reported significantly higher levels of insomnia than controls [74]. A Canadian longitudinal study found that adolescents who newly experienced cyber-victimization became more likely to report insufficient sleep duration at follow-up [75]. Similarly, a large national study among US high school students showed that electronically bullied females had inadequate sleep duration (fewer than 8 h on an average school night) [76]. Furthermore, there is consistent evidence that insomnia and sleep deprivation might precede, maintain or worsen psychotic symptoms over time [77,78,79]; and even precipitate the onset of psychotic episodes [80]. Some observations have also been made on the emergence of de novo perception abnormalities (e.g., distortions and hallucinations) in sleep deprived individuals with no history of psychiatric illness [81]. Insomnia has, for example, been associated with a 2- to 4-fold increase in the frequency of hallucinations in healthy individuals from the general population [82]. A multi-country study revealed that sleep disturbances were significantly linked to increased odds for at least one psychotic symptom [83].

The present research

The purpose of this paper is to contribute to the existing literature in more than one way. First, while expansive research has accumulated concerning the association between traditional, face-to-face peer victimization and psychosis among healthy emerging adults [34, 36, 42,43,44], a paucity of empirical research has been undertaken so far to investigate these associations with experiences of new and evolving ways of victimization through the digital world (e.g., [45,46,47,48]). Exploring these associations is highly relevant and timely, given that emerging adults are heavy users of digital devices and technologies [84,85,86], highly exposed to online risks and cyber forms of victimization [25, 26], and are at the peak age of onset of psychotic disorders [87]. Second, this study intends to provide the scientific community with a better understanding of the factors underlying the relationship between cyber-victimization and SRPEs. Determining the influence of mediators may help elucidate the relationship between these constructs, and assist in designing and implementing evidence-informed prevention and intervention strategies. Third, most of the available studies on the association victimization-psychosis (and more particularly, cybervictimization-psychosis) have emerged from Western countries, with no studies identified from the Middle Eastern and North African (MENA) countries. The prevalence, experiences, consequences and reactions to being cyber-victimized vary widely across cultures [88,89,90]. Similarly, the prevalence and features of SRPEs are culturally-dependent [91, 92], and seem to be over-represented in Arab populations [93, 94]. Hence the importance of international studies on the topic from two lower-middle income developing Arab countries of the MENA region, Tunisia (North African) and Lebanon (Middle Eastern). In this regard, we performed the current study to test the hypothesis that psychological distress and insomnia symptoms have a significant indirect mediating effect on the association between cyber- victimization and SRPEs in a binational sample of Tunisian and Lebanese community adults.

Method

The present study is part of a large cross-cultural, binational project including community-dwelling adults from Tunisia and Lebanon (The PEARLS project, [Psychotic Experiences in ARabs from Lebanon and tuniSia]). This project is aiming at validating the Arabic version of the Community Assessment of Psychic Experience (CAPE-42), as well as examining the nature and correlates of subclinical psychotic phenomena in these countries (for further details about the project, please see [95]). Participants have been invited to be part of our cross-sectional online study during June-September, 2022. Eligibility criteria involved: (1) being aged 18–35 years, (2) having no self-reported past personal history of physician-diagnosed mental illness, including psychosis, (3) having no prior antipsychotic drugs intake, and (4) willingness to participate. As such, participants with known mental disorders were excluded from our study. Data were collected using an online anonymous survey shared through social media networks (Facebook, Instagram, and WhatsApp). Detailed information about the purpose of the study were included in the informed consent form that was attached in the first page of the online survey. Participation was volunteer and no compensation was offered. We examined Internet protocol (IP) addresses in order to ensure that no respondent took the survey more than once. Ethics approval for this study was obtained from the Psychiatric Hospital of the Cross ethics committee (approval code: HPC-013-2022).

Questionnaire

The questionnaire was presented in the native language (Arabic) of respondents, required 15–20 min to complete, and was divided into two sections. The first section comprised items about demographic information, including age, gender, marital status, educational level, housing area, living arrangement, and substance use. Participants were also asked whether they have been previously diagnosed by a physician with any mental illness, including psychosis, and if they had any prior antipsychotic drugs intake. The second section contained four self-report scales (The Revised Cyber Bullying Inventory–II [RCBI-II], the Community Assessment of Psychic Experience-42 [CAPE-42] scale, the Depression Anxiety Stress Scale 8 (DASS-8), and the Insomnia Severity Index [ISI]).

The RCBI-II

This is a 20-item, four-point Likert self-report measure involving two subscales to precise either the indicated cyberbullying behavior happened to the respondent as a cyber-victim (cyber-victimization subscale, 10 items), or was perpetrated by them as a cyberbully (cyberbullying subscale, 10-items) [96]. Only the cyber-victimization subscale was used in the context of the present study, with higher scores indicating exposure to greater cyber-victimization experiences. The Arabic version of the RCBI-II was used [97]. Our sample yielded a McDonald’s omega value of 0.84 for the cyber-victimization subscale.

The CAPE-42

In this study, we used the positive dimension of the CAPE, which contains 20 out of 42 total items of the scale [98]. The positive CAPE dimension assesses positive SRPEs on a two-dimensional scale: (1) frequency of SRPEs and (2) degree of distress caused by them. This 20-item positive dimension can be divided into four types of positive SRPEs: Bizarre Experiences, Perceptual Abnormalities, Persecutory Ideation, and Magical Thinking. We only used the total scores of the frequency sub-dimension of the positive CAPE dimension, with scores ranging from 20 to 80. The Arabic version of scale yielded excellent psychometric properties [99], with McDonald’s omega value being calculated as 0.78 for the positive CAPE dimension subscale used in this study.

The DASS-8

The DASS-8 [100] is an Arabic version of the DASS, composed of eight items and three dimensions: anxiety (e.g., “felt scared without reason”; three items), depression (e.g., “felt down hearted and blue”; three items), and stress (e.g., “was using a lot of my mental energy”; two items). In the present sample, McDonald’s omega values were the following: depression (0.73), anxiety (0.73) and stress (0.65).

The ISI

This a reliable measure for evaluating the nature, severity and impact of insomnia symptoms [70]. It is composed of 7 self-report items assessing the following sleep parameters: sleep maintenance and early morning awakening problems, severity of sleep onset, noticeability of sleep problems by others, interference of sleep difficulties with daytime functioning, sleep dissatisfaction, and distress caused by the sleep difficulties. The Arabic version of the ISI has been used [72] (McDonald’s omega in this study = 0.82).

Statistical analysis

SPSS software version 23 was used to conduct data analysis. We had no missing data in our database. McDonald’s omega values were recorded for reliability analysis of all scales and subscales. The positive dimension score was normally distributed as its skewness and kurtosis values varied between − 1 and + 1 [101]; therefore, the Student t test was used to compare two means, ANOVA test to compare three or more means, and the Pearson test to correlate two continuous variables. To check for a significant indirect effect of insomnia severity/psychological distress between cyber-victimization and positive dimension, we conducted a mediation analysis using SPSS PROCESS v3.4 model 4 with three pathways; pathway A from the independent variable to the mediator, pathway B from the mediator to the dependent variable and pathway C from the independent to the dependent variable. Variables that showed a p < 0.25 in the bivariate analysis were entered in the path analysis. Significance was set at a p < 0.05.

Results

A total of 4158 Lebanese and 735 Tunisian participants filled the survey; 1055 Lebanese and 72 Tunisians were excluded for having self-reported mental physician-diagnosed mental health issues. Finally, the total sample was composed of 3766 participants; 3103 were from Lebanon and 663 from Tunisia. A higher mean age was significantly found in the Tunisian sample, whereas higher insomnia severity and psychological distress mean scores were significantly found in the Lebanese sample. No significant difference was found in terms of gender between the two groups. All sociodemographic and other characteristics of the participants are summarized in Table 1.

Table 1 Sociodemographic and other characteristics of the participants (N = 3103)

Bivariate analysis

The results of the bivariate analysis are summarized in Tables 2 and 3. Higher positive dimension scores were found in Lebanese participants compared to Tunisians, in single participants compared to married ones, in those with a university level of education compared to secondary or less, in those who live in rural areas compared to urban, in those who do not smoke, do not drink alcohol and do not use marijuana or any other illegal drug. Furthermore, more cyber-victimization, a higher insomnia severity and psychological distress were significantly associated with higher positive dimension scores. Finally, older age was significantly associated with lower positive dimension scores.

Table 2 Bivariate analysis of factors associated with the CAPE positive dimension
Table 3 Correlation of continuous variables with the CAPE positive dimension

Mediation analysis

The results of the mediation analysis showed that insomnia severity and psychological distress mediated the association between cyber-victimization and positive dimension (Table 4). Higher cyber-victimization was significantly associated with more insomnia severity/psychological distress, which were, in turn, significantly associated with more positive dimension. Finally, more cyber-victimization was significantly and directly associated with more positive dimension (Figs. 1 and 2).

Table 4 Mediation analyses results, taking the cyber-victimization score as the independent variable, insomnia severity/psychological distress as the mediator and positive dimension score as the dependent variable
Fig. 1
figure 1

(a) Relation between cyber-victimization and insomnia severity (R2 = .068); (b) Relation between insomnia severity and CAPE positive dimension (R2 = .283); (c) Total effect of cyber-victimization on positive psychotic experiences (R2 = .211); (c’) Direct effect of cyber-victimization on positive psychotic experiences. Numbers are displayed as regression coefficients (standard error). ***p < 0.001

Fig. 2
figure 2

(a) Relation between cyber-victimization and psychological distress (R2 = .118); (b) Relation between psychological distress and CAPE positive dimension (R2 = .304); (c) Total effect of cyber-victimization on positive psychotic experiences (R2 = .211); (c’) Direct effect of cyber-victimization on positive psychotic experiences. Numbers are displayed as regression coefficients (standard error). ***p < 0.001

Discussion

We build on the extent literature on face-to-face victimization to theorize about the nature and the mediating factors in the relationship between cybervictimization and psychosis proneness. As such, we sought to examine the hypothesized indirect effects of cybervictimization on SRPEs through insomnia and psychological distress. Findings indicate that our hypothesis is partly supported. After controlling for potential confounders (including country of origin, sociodemographic variables and substance use), analyses revealed that insomnia and distress symptoms were partial mediators of the relationship cybervictimization-SRPEs.

As for the direct effects, our results demonstrate that cybervictimization significantly and positively correlates with SRPEs in non-clinical individuals from the MENA region. These findings are in agreement with the limited existing literature. A study published in 2022 by Paruk et al. [45] surveyed South African adolescents aged 13–18 years, and showed that schizophrenia represented the second most frequent psychiatric diagnosis associated with cyber-victimization (57.1%), following major depressive disorder (72.4%). In another study by Magaud et al. [46] revealed that cyber-victimization, as assessed using self-developed questions, was highly prevalent (38%) among individuals at clinical high risk (CHR) for psychosis, and mostly received via text messages, instant messaging and Facebook. A recent Chinese study among high school students reported that involvement in cyberbullying either as victims or as bullies was significantly linked to SRPEs [47]; whereas a Turkish study among undergraduate students found that engaging in cyberbullying as a perpetrator was associated with greater psychoticism [48]. Our findings preliminarily confirm that the well-established relationship between victimization and psychosis would apply to the cyber form of victimization; and that this relationship also applies to other previously unexplored cultural backgrounds. However, given that our data is cross-sectional and that this is the first study to investigate cybervictimization in relation to psychotic symptoms in an Arab country from the MENA region, the present results should be considered tentative pending future longitudinal studies in the same context.

Regarding the indirect effects, we found, as expected, that the two theoretically-driven factors, i.e. psychological distress symptoms and insomnia severity, partially mediated the association between cybervictimization and SRPEs. This important finding is consistent with the fact that both psychological distress and sleep problems have been suggested as potential consequences of cyber-bullying [62, 63, 66, 73, 75]; and both have been hypothesized as precipitating and perpetuating risk factors for psychotic symptoms [102,103,104,105]. A mediator refers to an intermediate variable “which represents the generative mechanisms through which the focal independent variable is able to influence the dependent variable of interest” [106]. Mediators thus enable a comprehensive understanding of the mechanism linking cybervictimization to SRPEs. Findings cautiously suggest that untreated insomnia and distress symptoms might add additional vulnerability to cyber-victims, contributing thereafter to more severe positive psychotic symptoms. It is of note, however, that the relationship between cyberbullying, insomnia and SRPEs seem to be complex and multi-determined. Research found that sleep deprivation leads to decreased activity in brain areas of the theory of mind neural network and increased activity in areas involved in perceiving threatening approach, which, in turn, results in social withdrawal [107]. Sleep insufficiency has also been demonstrated to increase amygdala activation [108,109,110], which is involved in threat perception (e.g., [111, 112]). We thus suggest that insomnia may partly contribute to misinterpreting neutral or ambiguous stimuli in the cyber-environment as hostile and threatening. Interestingly, abnormal response to neutral stimuli during emotional processing tasks and increased activity in temporal cortex have also been reported in at -risk for psychosis populations [113]. This suggests that an individual with psychosis may experience neutral or benign cyber-communication as negatively directed toward them. These observations highlight that future research is needed to investigate neural mechanisms that may underscore the connection between cyberbullying, insomnia and SRPEs. More longitudinal studies are also required to elucidate the causal relationships between these variables. The future studies need to go beyond self-report measures and take into account behavioral/clinical aspects of cyberbullying, as well as objective measures of insomnia.

Limitations

Before drawing any conclusions from our findings, certain limitations need to be discussed. First, our data is cross-sectional; which implies that any estimations of mediation effects are correlational in nature, and the correct causal ordering assumption cannot be tested until longitudinal research is conducted. Second, the generalizability of findings may be limited, because our sample was based on a web-based convenience sampling. Third, our results may be subject to response biases due to self-report method effects. This may be a concern, especially since symptoms of insomnia, depression and anxiety may overlap (e.g., [114, 115]). To address this limitation, future studies need to consider using objective measures of sleep disturbances and structured clinical interviews to assess depression and anxiety levels. A fourth limitation lies to the fact that, expect for gender, all other sociodemographic variables (i.e., age, marital status, education level, housing area, living arrangement, substances use) were statistically significant between the Tunisian and Lebanese samples. These heterogeneous characteristics of the two samples might have affected our findings. We highlight, however, that all these factors were controlled for in the mediation analyses. Finally, further studies should consider investigating the role of other mediators on the interplay between cybervictimization and positive SRPEs, such as alexithymia and difficulties in emotional regulation [116,117,118].

Study implications

The current findings that cybervictimization is positively correlated with SRPEs add further support to the association between victimization, in general, and psychosis proneness. In addition, findings shed light on the significant indirect role of insomnia and distress in the cross-sectional link between cybervictimization and positive SRPEs. This preliminarily suggests that these psychopathological factors may be regarded as potential prevention and early-intervention targets for psychosis. Therefore, we recommend, with the caution appropriate to the cross-sectional design, that screening and monitoring for insomnia, depression, anxiety, and stress be incorporated into the routine mental health examination for individuals exposed to cybervictimization who present with SRPEs; and when appropriate, interventions should be delivered. Sufficient evidence has been adduced to confirm the effectiveness of sleep interventions, such as proper sleep hygiene and tracking [119], or Cognitive Behavioral Therapy for insomnia (CBTi) [120,121,122] in individuals with early and subthreshold psychosis (for review, see [104]). Interestingly, the CBTi has proven beneficial in improving attenuated psychotic symptoms [120, 123]. In this line of thinking, it has also been observed that antidepressants may have an antipsychotic action through improvement of mood state and reduction of inadequate appraisal of attenuated positive symptoms [124]. Fusar-Poli et al. [124] proposed that antidepressants could affect individuals’ psychosis risk by modulating their response to environmental stresses, either directly through neurochemicals implicated in controlling responses to stress, or indirectly by preventing anxiety/depression subsequent to these stresses. The above-mentioned interventions can act as buffers to prevent psychosis in cyber-victimized young people with pre-existing genetic predisposition.

Conclusion

The current research had denoted for the first time that insomnia and psychological distress have a possible mediating role in the cybervictimization/positive SRPEs connection. Identifying these mediators could provide novel insight for psychosis prevention efforts and intervention targets for cyber-victimized individuals prone to experience subclinical psychotic symptoms. Our findings also offer an empirical basis for future longitudinal research on the nature and mechanisms of the relationship between cyber forms of victimization and psychosis in healthy young individuals.

Data Availability

All data generated or analyzed during this study are not publicly available due the restrictions from the ethics committee. Reasonable requests can be addressed to the corresponding author.

References

  1. Oh H, DeVylder JE, Chen F-p. To treat or not to treat: responding to psychotic experiences. Br J Social Work. 2015;45(7):2003–19.

    Article  Google Scholar 

  2. Van Os J, Reininghaus U. Psychosis as a transdiagnostic and extended phenotype in the general population. World Psychiatry. 2016;15(2):118–24.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Van Os J, et al. A systematic review and meta-analysis of the psychosis continuum: evidence for a psychosis proneness–persistence–impairment model of psychotic disorder. Psychol Med. 2009;39(2):179–95.

    Article  PubMed  Google Scholar 

  4. Healy C, et al. Childhood psychotic experiences are associated with poorer global functioning throughout adolescence and into early adulthood. Acta psychiatrica Scandinavica. 2018;138(1):26–34.

    Article  CAS  PubMed  Google Scholar 

  5. Carey E et al. Evidence that infant and early childhood developmental impairments are associated with hallucinatory experiences: results from a large, population-based cohort study. Psychol Med, 2021: p. 1–9.

  6. Linscott R, Van Os J. An updated and conservative systematic review and meta-analysis of epidemiological evidence on psychotic experiences in children and adults: on the pathway from proneness to persistence to dimensional expression across mental disorders. Psychol Med. 2013;43(6):1133–49.

    Article  CAS  PubMed  Google Scholar 

  7. Yates K, et al. Hallucinations in the general population across the adult lifespan: prevalence and psychopathologic significance. Br J Psychiatry. 2021;219(6):652–8.

    Article  PubMed  Google Scholar 

  8. McGrath JJ, et al. Age of onset and lifetime projected risk of psychotic experiences: cross-national data from the World Mental Health Survey. Schizophr Bull. 2016;42(4):933–41.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Fekih-Romdhane F, et al. Prevalence and correlates of psychotic like experiences in a large community sample of young adults in Tunisia. Commun Ment Health J. 2020;56(6):991–1003.

    Article  Google Scholar 

  10. Healy C, et al. Childhood and adolescent psychotic experiences and risk of mental disorder: a systematic review and meta-analysis. Psychol Med. 2019;49(10):1589–99.

    Article  PubMed  Google Scholar 

  11. Knight C, et al. Prevalence of and recovery from common mental disorder including psychotic experiences in the UK primary care improving access to psychological therapies (IAPT) programme. J Affect Disord. 2020;272:84–90.

    Article  PubMed  Google Scholar 

  12. Bhavsar V, et al. A systematic review and meta-analysis of mental health service use in people who report psychotic experiences. Early Interv Psychiat. 2018;12(3):275–85.

    Article  Google Scholar 

  13. Rimvall MK, et al. Mental health service use and psychopharmacological treatment following psychotic experiences in preadolescence. Am J Psychiatry. 2020;177(4):318–26.

    Article  PubMed  Google Scholar 

  14. Moriyama TS, et al. Differences between self-reported psychotic experiences, clinically relevant psychotic experiences, and attenuated psychotic symptoms in the general population. Front Psychiatry. 2019;10:782.

    Article  PubMed  PubMed Central  Google Scholar 

  15. van Nierop M, et al. Phenotypically continuous with clinical psychosis, discontinuous in need for care: evidence for an extended psychosis phenotype. Schizophr Bull. 2012;38(2):231–8.

    Article  PubMed  Google Scholar 

  16. Kelleher I, et al. Are screening instruments valid for psychotic-like experiences? A validation study of screening questions for psychotic-like experiences using in-depth clinical interview. Schizophr Bull. 2011;37(2):362–9.

    Article  PubMed  Google Scholar 

  17. Kelleher I, et al. Clinicopathological significance of psychotic experiences in non-psychotic young people: evidence from four population-based studies. Br J Psychiatry. 2012;201(1):26–32.

    Article  PubMed  Google Scholar 

  18. Polanczyk G, et al. Etiological and clinical features of childhood psychotic symptoms: results from a birth cohort. Arch Gen Psychiatry. 2010;67(4):328–38.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Taylor MJ, et al. Heritability of psychotic experiences in adolescents and interaction with environmental risk. JAMA psychiatry. 2022;79(9):889–97.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Cheng SC, Walsh E, Schepp KG. Vulnerability, stress, and support in the disease trajectory from prodrome to diagnosed schizophrenia: diathesis–stress–support model. Arch Psychiatr Nurs. 2016;30(6):810–7.

    Article  PubMed  Google Scholar 

  21. Patchin JW, Hinduja S. Bullies move beyond the schoolyard: a preliminary look at cyberbullying. Youth violence and juvenile justice. 2006;4(2):148–69.

    Article  Google Scholar 

  22. Bauman S, Cross D, Walker J. Principles of cyberbullying research definition, methods, and measures, 2013: p. 2013.

  23. Kowalski RM, et al. Bullying in the digital age: a critical review and meta-analysis of cyberbullying research among youth. Psychol Bull. 2014;140(4):1073.

    Article  PubMed  Google Scholar 

  24. Gini G, Card NA, Pozzoli T. A meta-analysis of the differential relations of traditional and cyber‐victimization with internalizing problems. Aggressive Behav. 2018;44(2):185–98.

    Article  Google Scholar 

  25. Modecki KL, et al. Bullying prevalence across contexts: a meta-analysis measuring cyber and traditional bullying. J Adolesc Health. 2014;55(5):602–11.

    Article  PubMed  Google Scholar 

  26. Hamm MP, et al. Prevalence and effect of cyberbullying on children and young people: a scoping review of social media studies. JAMA Pediatr. 2015;169(8):770–7.

    Article  PubMed  Google Scholar 

  27. Hase CN, et al. Impacts of traditional bullying and cyberbullying on the mental health of middle school and high school students. Psychol Sch. 2015;52(6):607–17.

    Article  Google Scholar 

  28. Hinduja S, Patchin JW. Bullying, cyberbullying, and suicide. Archives of suicide research. 2010;14(3):206–21.

    Article  PubMed  Google Scholar 

  29. Ortuño-Sierra J, et al. Bullying, cyberbullying and mental health: the role of student connectedness as a school protective factor. Psychosocial Intervention. 2022;31(1):33–41.

    PubMed  PubMed Central  Google Scholar 

  30. Fossum S et al. The significance of traditional bullying, cyberbullying, and Mental Health problems for Middle School Students feeling unsafe in the School Environment. Scandinavian J Educational Res, 2021: p. 1–13.

  31. Lee J, et al. Face-to-face bullying, cyberbullying, and multiple forms of substance use among school-age adolescents in the USA. School mental health. 2018;10(1):12–25.

    Article  Google Scholar 

  32. Landstedt E, Persson S. Bullying, cyberbullying, and mental health in young people. Scand J Public Health. 2014;42(4):393–9.

    Article  PubMed  Google Scholar 

  33. Olweus D, Limber SP. Some problems with cyberbullying research. Curr Opin Psychol. 2018;19:139–43.

    Article  PubMed  Google Scholar 

  34. van Dam DS, et al. Childhood bullying and the association with psychosis in non-clinical and clinical samples: a review and meta-analysis. Psychol Med. 2012;42(12):2463–74.

    Article  PubMed  Google Scholar 

  35. Cunningham T, Hoy K, Shannon C. Does childhood bullying lead to the development of psychotic symptoms? A meta-analysis and review of prospective studies. Psychosis. 2016;8(1):48–59.

    Article  Google Scholar 

  36. Catone G, et al. Bullying victimisation and risk of psychotic phenomena: analyses of british national survey data. The Lancet Psychiatry. 2015;2(7):618–24.

    Article  PubMed  Google Scholar 

  37. Fekih-Romdhane F, Cheour M. Harcèlement scolaire chez les sujets à ultra haut risque de psychose. In Annales Médico-psychologiques, revue psychiatrique. Elsevier; 2022.

  38. Resett S, Gamez-Guadix M. Traditional bullying and cyberbullying: differences in emotional problems, and personality. Are cyberbullies more Machiavellians? J Adolesc. 2017;61:113–6.

    Article  PubMed  Google Scholar 

  39. Dooley JJ, Pyżalski J, Cross D. Cyberbullying versus face-to-face bullying: a theoretical and conceptual review. Z für Psychologie/Journal Psychol. 2009;217(4):182.

    Article  Google Scholar 

  40. Tokunaga RS. Following you home from school: a critical review and synthesis of research on cyberbullying victimization. Comput Hum Behav. 2010;26(3):277–87.

    Article  Google Scholar 

  41. Sticca F, Perren S. Is cyberbullying worse than traditional bullying? Examining the differential roles of medium, publicity, and anonymity for the perceived severity of bullying. J Youth Adolesc. 2013;42(5):739–50.

    Article  PubMed  Google Scholar 

  42. Boden JM, et al. Bullying victimization in adolescence and psychotic symptomatology in adulthood: evidence from a 35-year study. Psychol Med. 2016;46(6):1311–20.

    Article  CAS  PubMed  Google Scholar 

  43. Catone G, et al. Bullying victimisation and psychosis: the interdependence and independence of risk trajectories. BJPsych Adv. 2017;23(6):397–406.

    Article  Google Scholar 

  44. Peh OH, Rapisarda A, Lee J. Childhood adversities in people at ultra-high risk (UHR) for psychosis: a systematic review and meta-analysis. Psychol Med. 2019;49(7):1089–101.

    Article  PubMed  Google Scholar 

  45. Paruk ME, Nassen R. Cyberbullying perpetration and victimisation amongst adolescent psychiatric patients at Lentegeur Hospital, South Africa. South Afr J psychiatry. 2022;28:1755.

    Google Scholar 

  46. Magaud E, Nyman K, Addington J. Cyberbullying in those at clinical high risk for psychosis. Early Interv Psychiat. 2013;7(4):427–30.

    Article  Google Scholar 

  47. Otake Y, Luo X. Psychotic-like Experiences Associated with Cyber and traditional bullying. Health Behav Policy Rev. 2019;6(2):192–8.

    Article  Google Scholar 

  48. Arıcak OT. Psychiatric symptomatology as a predictor of cyberbullying among university students Eurasian Journal of Educational Research (EJER), 2009(34).

  49. Isohanni M, et al. Childhood and adolescent predictors of schizophrenia in the Northern Finland 1966 Birth Cohort–a descriptive life-span model. Eur Arch Psychiatry Clin NeuroSci. 2000;250:311–9.

    Article  CAS  PubMed  Google Scholar 

  50. Wright M. Cyberbullying victimization through social networking sites and adjustment difficulties: the role of parental mediation. J Association Inform Syst. 2018;19(2):1.

    Google Scholar 

  51. Arató N, et al. Cybervictimization and cyberbullying: the role of socio-emotional skills. Front Psychiatry. 2020;11:248.

    Article  PubMed  PubMed Central  Google Scholar 

  52. Subramanian L. Socio-emotional functioning of psychosis-prone individuals in structured and unstructured social settings. Central Michigan University; 2006.

  53. Debbané M, et al. Attachment, neurobiology, and mentalizing along the psychosis continuum. Front Hum Neurosci. 2016;10:406.

    Article  PubMed  PubMed Central  Google Scholar 

  54. Canestrari C et al. Parental attachment and cyberbullying victims: the mediation effect of gelotophobia. Curr Psychol, 2021: p. 1–12.

  55. Heinz A, Deserno L, Reininghaus U. Urbanicity, social adversity and psychosis. World Psychiatry. 2013;12(3):187–97.

    Article  PubMed  PubMed Central  Google Scholar 

  56. Görzig A. Who bullies and who is bullied online?: A study of 9–16 year old internet users in 25 European countries 2011.

  57. Olenik-Shemesh D, Heiman T. Cyberbullying victimization in adolescents as related to body esteem, social support, and social self-efficacy. J Genet Psychol. 2017;178(1):28–43.

    Article  PubMed  Google Scholar 

  58. Wüsten C, Lincoln TM. The association of family functioning and psychosis proneness in five countries that differ in cultural values and family structures. Psychiatry Res. 2017;253:158–64.

    Article  PubMed  Google Scholar 

  59. Shakoor S, et al. A shared genetic propensity underlies experiences of bullying victimization in late childhood and self-rated paranoid thinking in adolescence. Schizophr Bull. 2015;41(3):754–63.

    Article  PubMed  Google Scholar 

  60. Borges S, Gayer-Anderson C, Mondelli V. A systematic review of the activity of the hypothalamic–pituitary–adrenal axis in first episode psychosis. Psychoneuroendocrinology. 2013;38(5):603–11.

    Article  CAS  PubMed  Google Scholar 

  61. González-Cabrera J, et al. Relationship between cyberbullying roles, cortisol secretion and psychological stress. Comput Hum Behav. 2017;70:153–60.

    Article  Google Scholar 

  62. Li C, et al. Traditional bullying and cyberbullying in the digital age and its associated mental health problems in children and adolescents: a meta-analysis. European Child & Adolescent Psychiatry; 2022. pp. 1–15.

  63. Yuchang J, et al. The differential victimization associated with depression and anxiety in cross-cultural perspective: a meta-analysis. Volume 20. Trauma; 2019. pp. 560–73. 4Abuse.

  64. Williams KD, Carter-Sowell AR. Marginalization through social ostracism: Effects of being ignored and excluded Coping with minority status: Responses to exclusion and inclusion, 2009: p. 104–122.

  65. Jang H, Song J, Kim R. Does the offline bully-victimization influence cyberbullying behavior among youths? Application of general strain theory. Comput Hum Behav. 2014;31:85–93.

    Article  Google Scholar 

  66. Alhujailli A, et al. Affective and stress consequences of cyberbullying. Symmetry. 2020;12(9):1536.

    Article  Google Scholar 

  67. Fusar-Poli P, et al. Comorbid depressive and anxiety disorders in 509 individuals with an at-risk mental state: impact on psychopathology and transition to psychosis. Schizophr Bull. 2014;40(1):120–31.

    Article  PubMed  Google Scholar 

  68. Devylder J, et al. Temporal association of stress sensitivity and symptoms in individuals at clinical high risk for psychosis. Psychol Med. 2013;43(2):259–68.

    Article  CAS  PubMed  Google Scholar 

  69. Fowler D, et al. Negative cognition, depressed mood, and paranoia: a longitudinal pathway analysis using structural equation modeling. Schizophr Bull. 2012;38(5):1063–73.

    Article  PubMed  Google Scholar 

  70. Wiles NJ, et al. Self-reported psychotic symptoms in the general population: results from the longitudinal study of the British National Psychiatric Morbidity Survey. Br J Psychiatry. 2006;188(6):519–26.

    Article  PubMed  Google Scholar 

  71. Weiser M, et al. Dysthymia in male adolescents is associated with increased risk of later hospitalization for psychotic disorders: a historical-prospective cohort study. Early Interv Psychiat. 2008;2(2):67–72.

    Article  Google Scholar 

  72. Kwon M, et al. Sleep quality as a mediator of the Relationship between Cyber victimization and depression. J Nurs Scholarsh. 2020;52(4):416–25.

    Article  PubMed  PubMed Central  Google Scholar 

  73. Sourander A, et al. Psychosocial risk factors associated with cyberbullying among adolescents: a population-based study. Arch Gen Psychiatry. 2010;67(7):720–8.

    Article  PubMed  Google Scholar 

  74. Kubiszewski V, et al. Cyber-bullying in adolescents: associated psychosocial problems and comparison with school bullying. L’encephale. 2012;39(2):77–84.

    Article  PubMed  Google Scholar 

  75. Patte KA, Qian W, Leatherdale ST. Modifiable predictors of insufficient sleep durations: a longitudinal analysis of youth in the COMPASS study. Prev Med. 2018;106:164–70.

    Article  PubMed  Google Scholar 

  76. Hertz MF, et al. Association between bullying victimization and health risk behaviors among high school students in the United States. J Sch Health. 2015;85(12):833–42.

    Article  PubMed  PubMed Central  Google Scholar 

  77. Lunsford-Avery JR, et al. Actigraphic-measured sleep disturbance predicts increased positive symptoms in adolescents at ultra high-risk for psychosis: a longitudinal study. Schizophr Res. 2015;164(1–3):15–20.

    Article  PubMed  PubMed Central  Google Scholar 

  78. Reeve S, Bell V. Sleep disorders predict the 1-year onset, persistence, but not remission of psychotic experiences in preadolescence: a longitudinal analysis of the ABCD cohort data. European Child & Adolescent Psychiatry; 2022. pp. 1–11.

  79. Reeve S, et al. Insomnia, negative affect, and psychotic experiences: modelling pathways over time in a clinical observational study. Psychiatry Res. 2018;269:673–80.

    Article  PubMed  PubMed Central  Google Scholar 

  80. Bauer M, et al. Temporal relation between sleep and mood in patients with bipolar disorder. Bipolar Disord. 2006;8(2):160–7.

    Article  PubMed  Google Scholar 

  81. Waters F, et al. Severe sleep deprivation causes hallucinations and a gradual progression toward psychosis with increasing Time Awake. Front Psychiatry. 2018;9:303.

    Article  PubMed  PubMed Central  Google Scholar 

  82. Sheaves B, et al. Insomnia and hallucinations in the general population: findings from the 2000 and 2007 british Psychiatric morbidity surveys. Psychiatry Res. 2016;241:141–6.

    Article  PubMed  PubMed Central  Google Scholar 

  83. Koyanagi A, Stickley A. The association between sleep problems and psychotic symptoms in the General Population: A Global Perspective. Sleep. 2015;38(12):1875–85.

    Article  PubMed  PubMed Central  Google Scholar 

  84. Statista. Global Gen Z Online Activity Reach by Device 2018. 2019, Statista.

  85. Lenhart A, et al. Social Media & Mobile Internet use among teens and young adults. Millennials. Pew internet & American life project; 2010.

  86. Anderson M, Jiang J. Teens, social media & technology 2018 Pew Research Center, 2018. 31(2018): p. 1673–1689.

  87. Solmi M, et al. Age at onset of mental disorders worldwide: large-scale meta-analysis of 192 epidemiological studies. Mol Psychiatry. 2022;27(1):281–95.

    Article  CAS  PubMed  Google Scholar 

  88. Eristi B. Reactions victims display against Cyberbullying: a cross-cultural comparison. Int J Contemp Educational Res. 2019;6(2):426–37.

    Article  Google Scholar 

  89. Baek J, Bullock LM. Cyberbullying: a cross-cultural perspective. Emotional and behavioural difficulties. 2014;19(2):226–38.

    Article  Google Scholar 

  90. Li Q. A cross-cultural comparison of adolescents’ experience related to cyberbullying. Educational Res. 2008;50(3):223–34.

    Article  Google Scholar 

  91. Wüsten C, et al. Psychotic experiences and related distress: a cross-national comparison and network analysis based on 7141 participants from 13 countries. Schizophr Bull. 2018;44(6):1185–94.

    Article  PubMed  PubMed Central  Google Scholar 

  92. Vermeiden M, et al. Cultural differences in positive psychotic experiences assessed with the Community Assessment of psychic Experiences-42 (CAPE-42): a comparison of student populations in the Netherlands, Nigeria and Norway. BMC Psychiatry. 2019;19(1):1–15.

    Article  Google Scholar 

  93. Fekih-Romdhane F, et al. Prevalence and risk factors of self‐reported psychotic experiences among high school and college students: a systematic review, meta‐analysis, and meta‐regression. Acta Psychiatrica Scandinavica; 2022.

  94. Obermeyer CM, Bott S, Sassine AJ. Arab adolescents: health, gender, and Social Context. J Adolesc Health. 2015;57(3):252–62.

    Article  PubMed  Google Scholar 

  95. Fekih-Romdhane F, Malaeb D, Loch AA, Farah N, Stambouli M, Cheour M, Obeid S, Hallit S. Problematic Smartphone Use Mediates the Pathway from Suicidal Ideation to Positive Psychotic Experiences: a Large Cross-Sectional, Population-Based Study. Int J Ment Health Addict. 2023 Feb 15:1–18. https://doi.org/10.1007/s11469-023-01028-8.

  96. Topcu Ç, Erdur-Baker Ö. RCBI-II: the second revision of the revised cyber bullying inventory. Meas Evaluation Couns Dev. 2018;51(1):32–41.

    Article  Google Scholar 

  97. Alrajeh SM, et al. An investigation of the relationship between cyberbullying, cybervictimization and depression symptoms: a cross sectional study among university students in Qatar. PLoS ONE. 2021;16(12):e0260263.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  98. Konings M, et al. Validity and reliability of the CAPE: a self-report instrument for the measurement of psychotic experiences in the general population. Acta psychiatrica Scandinavica. 2006;114(1):55–61.

    Article  CAS  PubMed  Google Scholar 

  99. Fekih-Romdhane F, Malaeb FN, Cheour D, Obeid M, Hallit S. S., Validation of the Arabic version of the Community Assessment of Psychic Experiences (CAPE-42) in a large sample of young adults from the general population Int J Ment Health Addict, 2023. In Press.

  100. Ali AM et al. The Depression Anxiety Stress Scale 21: Development and Validation of the Depression Anxiety Stress Scale 8-Item in Psychiatric Patients and the General Public for Easier Mental Health Measurement in a Post COVID-19 World Int J Environ Res Public Health, 2021. 18(19).

  101. Hair JF Jr, et al. A primer on partial least squares structural equation modeling (PLS-SEM). Sage publications; 2021.

  102. Reeve S, Sheaves B, Freeman D. The role of sleep dysfunction in the occurrence of delusions and hallucinations: a systematic review. Clin Psychol Rev. 2015;42:96–115.

    Article  PubMed  PubMed Central  Google Scholar 

  103. Waite F, et al. Sleep and schizophrenia: from epiphenomenon to treatable causal target. Schizophr Res. 2020;221:44–56.

    Article  PubMed  PubMed Central  Google Scholar 

  104. Fekih-Romdhane F, Hallit S, Cheour M, Jahrami H. The nature, consequences, mechanisms, and management of sleep disturbances in individuals at-risk for psychosis. Front Psychiatry. 2022 Sep 20;13:1011963. https://doi.org/10.3389/fpsyt.2022.1011963.

  105. Tzang RF, Chang CH, Chang YC. Adolescent’s psychotic-like symptoms associated with internet addiction. J Neuropsychiatry Clin Neurosci. 2015;69(6):384–4.

    Google Scholar 

  106. Baron RM, Kenny DA. The moderator–mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. J Personal Soc Psychol. 1986;51(6):1173.

    Article  CAS  Google Scholar 

  107. Ben Simon E, Walker MP. Sleep loss causes social withdrawal and loneliness. Nat Commun. 2018;9(1):3146.

    Article  PubMed  PubMed Central  Google Scholar 

  108. Krause AJ, et al. The sleep-deprived human brain. Nat Rev Neurosci. 2017;18(7):404–18.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  109. Yoo SS, et al. The human emotional brain without sleep–a prefrontal amygdala disconnect. Curr Biol. 2007;17(20):R877–8.

    Article  CAS  PubMed  Google Scholar 

  110. Motomura Y, et al. Sleep debt elicits negative emotional reaction through diminished amygdala-anterior cingulate functional connectivity. PLoS ONE. 2013;8(2):e56578.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  111. Fox AS, Shackman AJ. The central extended amygdala in fear and anxiety: closing the gap between mechanistic and neuroimaging research. Neurosci Lett. 2019;693:58–67.

    Article  CAS  PubMed  Google Scholar 

  112. Shackman AJ, et al. The neurobiology of dispositional negativity and attentional biases to threat: implications for understanding anxiety disorders in adults and youth. J Exp Psychopathol. 2016;7(3):311–42.

    Article  PubMed  PubMed Central  Google Scholar 

  113. Kozhuharova P, et al. Neural correlates of social cognition in populations at risk of psychosis: a systematic review. Neurosci Biobehavioral Reviews. 2020;108:94–111.

    Article  CAS  Google Scholar 

  114. Victor R, Garg S, Gupta R. Insomnia and depression: how much is the overlap? Indian J Psychiatry. 2019;61(6):623–9.

    Article  PubMed  PubMed Central  Google Scholar 

  115. Ghani SB, et al. Associations between Insomnia symptoms and anxiety symptoms in adults in a community sample of Southeastern Pennsylvania, USA. Diseases. 2022;10(4):92.

    Article  PubMed  PubMed Central  Google Scholar 

  116. Shabahang R, et al. Role of difficulties in emotional regulation and alexithymia in prediction of bullying. Q J Child Mental Health. 2019;6(3):40–50.

    Article  Google Scholar 

  117. Vines L, et al. Elevated emotion reactivity and emotion regulation in individuals at clinical high risk for developing psychosis and those diagnosed with a psychotic disorder. Early Interv Psychiat. 2022;16(7):724–35.

    Article  Google Scholar 

  118. O’Driscoll C, Laing J, Mason O. Cognitive emotion regulation strategies, alexithymia and dissociation in schizophrenia, a review and meta-analysis. Clin Psychol Rev. 2014;34(6):482–95.

    Article  PubMed  Google Scholar 

  119. Griffiths C, et al. A qualitative study of early intervention psychosis (EIP) service patient’s experience of Sleep, Exercise, Sleep Hygiene advice and Fitbit Wearable Activity and Sleep Tracker. Open J Psychiatry. 2021;11(2):91–106.

    Article  Google Scholar 

  120. Freeman D, et al. The effects of improving sleep on mental health (OASIS): a randomised controlled trial with mediation analysis. The Lancet Psychiatry. 2017;4(10):749–58.

    Article  PubMed  PubMed Central  Google Scholar 

  121. Bradley J, et al. Treating sleep problems in young people at ultra-high risk of psychosis: a feasibility case series. Behav Cogn Psychother. 2018;46(3):276–91.

    Article  PubMed  Google Scholar 

  122. Myers E, Startup H, Freeman D. Cognitive behavioural treatment of insomnia in individuals with persistent persecutory delusions: a pilot trial. J Behav Ther Exp Psychiatry. 2011;42(3):330–6.

    Article  PubMed  PubMed Central  Google Scholar 

  123. Freeman D, et al. Efficacy of cognitive behavioural therapy for sleep improvement in patients with persistent delusions and hallucinations (BEST): a prospective, assessor-blind, randomised controlled pilot trial. The Lancet Psychiatry. 2015;2(11):975–83.

    Article  PubMed  PubMed Central  Google Scholar 

  124. Fusar-Poli P, Valmaggia L, McGuire P. Can antidepressants prevent psychosis? The Lancet. 2007;370(9601):1746–8.

    Article  Google Scholar 

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FFR, SO and SH designed the study; FFR drafted the manuscript; DM and MS collected the data; SH carried out the analysis and interpreted the results; NF and MC reviewed the paper for intellectual content; all authors reviewed the final manuscript and gave their consent.

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Correspondence to Feten Fekih-Romdhane or Souheil Hallit.

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Fekih-Romdhane, F., Stambouli, M., Malaeb, D. et al. Insomnia and distress as mediators on the relationship from cyber-victimization to self-reported psychotic experiences: a binational study from Tunisia and Lebanon. BMC Psychiatry 23, 524 (2023). https://doi.org/10.1186/s12888-023-05019-w

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